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ORCIDWilliam D'Amico 0001
Person information
- affiliation: Politecnico di Milano, Milano, Italy
Other persons with the same name
- William D'Amico 0002 — John Hopkins University, MD, USA
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Journal Articles
- 2024
[j3]William D'Amico
, Alessio La Bella, Marcello Farina:
An Incremental Input-to-State Stability Condition for a Class of Recurrent Neural Networks. IEEE Trans. Autom. Control. 69(4): 2221-2236 (2024)- 2023
- [j2]William D'Amico, Marcello Farina:
Virtual reference feedback tuning for linear discrete-time systems with robust stability guarantees based on set membership. Autom. 157: 111228 (2023) - [j1]William D'Amico, Andrea Bisoffi, Marcello Farina:
Data-Based Control Design for Output-Error Linear Discrete-Time Systems With Probabilistic Stability Guarantees. IEEE Control. Syst. Lett. 7: 2035-2040 (2023)
Conference and Workshop Papers
- 2024
- [c3]William D'Amico, Simone Zanini, Alessio La Bella, Marcello Farina:
LMI-Based Control Design with Robust Local Stability Guarantees for Linear Discrete-Time Systems with Input Saturations. ECC 2024: 3490-3495 - 2022
- [c2]William D'Amico, Marcello Farina:
Data-based control design for linear discrete-time systems with robust stability guarantees. CDC 2022: 1429-1434 - [c1]William D'Amico, Marcello Farina, Giulio Panzani:
Recurrent Neural Network controllers learned using Virtual Reference Feedback Tuning with application to an Electronic Throttle Body. ECC 2022: 2137-2142
Informal and Other Publications
- 2024
- [i4]Alessio La Bella, Marcello Farina, William D'Amico, Luca Zaccarian:
Regional stability conditions for recurrent neural network-based control systems. CoRR abs/2409.15792 (2024) - 2022
- [i3]William D'Amico, Marcello Farina:
Virtual Reference Feedback Tuning for linear discrete-time systems with robust stability guarantees based on Set Membership. CoRR abs/2203.00088 (2022) - [i2]William D'Amico, Alessio La Bella, Marcello Farina:
An incremental input-to-state stability condition for a generic class of recurrent neural networks. CoRR abs/2210.09721 (2022) - 2021
- [i1]William D'Amico, Marcello Farina, Giulio Panzani:
Advanced control based on Recurrent Neural Networks learned using Virtual Reference Feedback Tuning and application to an Electronic Throttle Body (with supplementary material). CoRR abs/2103.02567 (2021)
Coauthor Index
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